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Exploration at the High-Energy Frontier: ATLAS Run 2 Searches Investigating the Exotic Jungle Beyond the Standard Model
No full textBouhova-Thacker, Evelina/0000-0002-5103-1558; Lloyd, Stephen/0000-0002-5073-2264; Morii, Masahiro/0000-0001-9324-057X; Bruschi, Marco/0000-0002-4319-4023; Vecchio, Valentina/0000-0002-1351-6757; Rousseau, David/0000-0001-7613-8063; Su, Dong/0000-0001-6980-0215; Gwilliam, Carl/0000-0002-9401-5304; Beau, Tristan/0000-0002-2022-2140; Hance, Michael/0000-0001-8392-0934; Winter, Benedict Tobias/0000-0001-9606-7688; Munoz Sanchez, Francisca/0000-0002-6374-458X; Worm, Steven/0000-0002-3865-4996; Mondal, Santu/0000-0002-6965-7380; Sampsonidou, Despoina/0000-0003-0384-7672; Mitsou, Vasiliki A./0000-0002-1533-8886; Stanislaus, Beojan/0000-0001-9007-7658; Grinstein, Sebastian/0000-0002-6460-8694; Vincter, Manuella/0000-0002-5338-8972; Doglioni, Caterina/0000-0002-1509-0390; Jia, Jiangyong/0000-0002-5725-3397; Cardillo, Fabio/0000-0002-4478-3524; Cunha Sargedas Sousa, Mario Jose/0000-0001-7991-593X; Bella, Gideon/0000-0002-4009-0990; Cristoforetti, Marco/0000-0002-0127-1342; Mckee, Shawn/0000-0002-4551-4502; Smirnova, Oxana/0000-0003-2517-531X; Stark, Giordon/0000-0001-6616-3433; Berta, Peter/0000-0003-0780-0345; D'Uffizi, Matteo/0000-0003-2499-1649; Koch, Simon Florian/0000-0002-2676-2842; Kumar, Mukesh/0000-0003-3681-1588; Sahinsoy, Merve/0000-0002-7400-7286; Di Luca, Andrea/0000-0002-9074-2133; Fox, Harald/0000-0003-3089-6090; Nikolopoulos, Konstantinos/0000-0002-3048-489X; Lacasta, Carlos/0000-0002-2623-6252; Merlassino, Claudia/0000-0002-5445-5938; Cheong, Sanha/0000-0002-2797-6383; Meloni, Federico/0000-0001-7075-2214; Terzo, Stefano/0000-0003-3388-3906; Rompotis, Nikolaos/0000-0003-2577-1875; Kretzschmar, Jan/0000-0002-8515-1355; Bhatta, Somadutta/0000-0002-9045-3278; Dong, Qichen/0000-0002-0117-7831; Konstantinidis, Nikolaos/0000-0002-4140-6360; Schmitt, Stefan/0000-0001-8387-1853; Beck, Hans Peter/0000-0001-7212-1096; Gaudio, Gabriella/0000-0002-6833-0933; Alimonti, Gianluca/0000-0002-7128-9046; Pleier, Marc-Andre/0000-0002-9461-3494; De La Torre Perez, Hector/0000-0002-4516-5269; Citron, Zvi/0000-0003-1831-6452; Azuelos, Georges/0000-0003-4241-022X; Quinn, Ryan/0000-0002-0879-6045; Butterworth, Jonathan/0000-0002-5905-5394; Klein, Lucas/0000-0002-0145-4747; Keeler, Richard/0000-0002-0510-4189; Kirk, Julie/0000-0001-8096-7577; Price, Darren/0000-0003-2750-9977; Bahmani, Marzieh/0000-0003-4173-0926; Pettee, Mariel/0000-0001-9208-3218; Schenck, Ferdinand/0000-0001-8279-4753; Redlinger, George/0000-0002-6437-9991; Mete, Alaettin Serhan/0000-0002-5508-530X; Martoiu, Sorin/0000-0002-4963-9441; Mcpherson, Robert/0000-0001-9211-7019; Held, Alexander/0000-0002-8924-5885; Kontaxakis, Pantelis/0000-0002-4860-5979; Schultz-Coulon, Hans-Christian/0000-0002-0860-7240; Martinez-Agullo, Pablo/0000-0001-8925-9518; Novak, Tadej/0000-0002-3053-0913; Islam, Wasikul/0000-0002-5624-5934; Elsing, Markus/0000-0002-1213-0545; Kaji, Toshiaki/0000-0002-6532-7501; Mindur, Bartosz/0000-0002-5511-2611; Leblanc, Matt/0000-0001-5977-6418; Kowalewski, Robert/0000-0002-7314-0990This report presents a comprehensive collection of searches for new physics performed by the ATLAS Collaboration during the Run 2 period of data taking at the Large Hadron Collider, from 2015 to 2018, corresponding to about 140 fb(-1) of root s = 13 TeV proton-proton collision data. These searches cover a variety of beyond-the-standard model topics such as dark matter candidates, new vector bosons, hidden-sector particles, leptoquarks, or vector-like quarks, among others. Searches for supersymmetric particles or extended Higgs sectors are explicitly excluded as these are the subject of separate reports by the Collaboration. For each topic, the most relevant searches are described, focusing on their importance and sensitivity and, when appropriate, highlighting the experimental techniques employed. In addition to the description of each analysis, complementary searches are compared, and the overall sensitivity of the ATLAS experiment to each type of new physics is discussed. Summary plots and statistical combinations of multiple searches are included whenever possible. (c) 2024 CERN for the benefit of the ATLAS Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW; FWF, Austria; ANAS; CNPq; FAPESP, Brazil; NSERC; CFI, Canada; NSFC, China; MEYS CR, Czech Republic; DNRF; DNSRC, Denmark; IN2P3-CNRS; CEA-DRF/IRFU, France; BMBF; MPG, Germany; RGC and Hong Kong SAR, China; ISF; Benoziyo Center, Israel; INFN, Italy; MEXT; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; SRC; Wallenberg Foundation, Sweden; SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; STFC/UKRI, United Kingdom; DOE; NSF, United States of America; BCKDF; CANARIE; CRC; DRAC, Canada [PRIMUS 21/SCI/017, UNCE SCI/013]; Czech Republic; ERC; ERDF; Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex; ANR, France; DFG; AvH Foundation, Germany - EU-ESF; Greek NSRF, Greece; BSF-NSF; NCN [UMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187]; La Caixa Banking Foundation; CERCA Programme Generalitat de Catalunya; PROMETEO [CIDEGENT/2019/023, CIDEGENT/2019/027]; Generalitat Valenciana, Spain [IDIFEDER/2018/048, NextGenEU PCI2022-135018-2]; Goran Gustafssons Stiftelse, Sweden; Royal Society [NIF-R1-231091]; Leverhulme Trust, United Kingdom; CERN: European Organization for Nuclear Research (CERN PJAS); Chile: Agencia Nacional de Investigacion y Desarrollo (FONDECYT) [1190886]; FONDECYT [1230987]; China: Chinese Ministry of Science and Technology [MOST-2023YFA1605700]; National Natural Science Foundation of China [NSFC -12175119, NSFC 12275265, NSFC-12075060]; Czech Republic: PRIMUS Research Programme [PRIMUS/21/SCI/017]; EU [ERC -101002463]; European Union: European Research Council [ERC -948254, ERC 101089007, MUCCA -CHIST-ERA-19-XAI-00]; European Union [FAIR-NextGenerationEU PE00000013]; Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC); France: Agence Nationale de la Recherche [ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-21-CE31-0022, ANR-22-EDIR-0002]; Investissements d'Avenir Labex; Germany: Baden-Wurttemberg Stiftung; Deutsche Forschungsgemeinschaft, Germany [DFG -469666862, DFG -CR 312/5-2]; Ministero dell'Universita e della Ricerca [PRIN -20223N7F8K -PNRR M4.C2.1.1]; Japan Society for the Promotion of Science (JSPS KAKENHI) [JP21H05085, JP22H01227, JP22H04944, JP22KK0227, RCN-314472]; Polish National Agency for Academic Exchange [PPN/PPO/2020/1/00002/U/00001]; Polish National Science Centre (NCN) [2021/42/E/ST2/00350]; NCN OPUS [2022/47/B/ST2/03059]; Slovenian Research Agency [J1-3010]; BBVA Foundation [LEO22-1-603]; MICIN FEDER [PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273-I, RYC2022-038164-I]; Swedish Research Council [VR 2018-00482, VR 2022-03845, VR 2022-04683]; VR [2021-03651]; Knut and Alice Wallenberg Foundation, Sweden [KAW 2017.0100, KAW 2018.0157, KAW 2018.0458, KAW 2019.0447, SNSF -PCEFP2_194658]; United Kingdom: Leverhulme Trust (Leverhulme Trust) [RPG-2020-004]; Neubauer Family FoundationWe gratefully acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW, Poland; FCT, Portugal; MNE/IFA, Romania; MESTD, Serbia; MSSR, Slovakia; ARIS and MVZI, Slovenia; DSI/NRF, South Africa; MICIU/AEI, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; TENMAK, Turkiye; STFC/UKRI, United Kingdom; DOE and NSF, United States of America. Individual groups and members have received support from BCKDF, CANARIE, CRC and DRAC, Canada; CERN-CZ, PRIMUS 21/SCI/017 and UNCE SCI/013, Czech Republic; COST, ERC, ERDF, Horizon 2020, ICSC-NextGenerationEU and Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; Norwegian Financial Mechanism 2014-2021, Norway; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. In addition, individual members wish to acknowledge support from CERN: European Organization for Nuclear Research (CERN PJAS); Chile: Agencia Nacional de Investigacion y Desarrollo (FONDECYT 1190886, FONDECYT 1210400, FONDECYT 1230812, FONDECYT 1230987); China: Chinese Ministry of Science and Technology (MOST-2023YFA1605700), National Natural Science Foundation of China (NSFC -12175119, NSFC 12275265, NSFC-12075060); Czech Republic: PRIMUS Research Programme (PRIMUS/21/SCI/017); EU: H2020 European Research Council (ERC -101002463); European Union: European Research Council (ERC -948254, ERC 101089007), Horizon 2020 Framework Programme (MUCCA -CHIST-ERA-19-XAI-00), European Union, Future Artificial Intelligence Research (FAIR-NextGenerationEU PE00000013), Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC, NextGenerationEU); France: Agence Nationale de la Recherche (ANR-20-CE31-0013, ANR-21-CE31-0013, ANR-21-CE31-0022, ANR-22-EDIR-0002), Investissements d'Avenir Labex (ANR-11-LABX-0012); Germany: Baden-Wurttemberg Stiftung (BW Stiftung-Postdoc Eliteprogramme), Deutsche Forschungsgemeinschaft, Germany (DFG -469666862, DFG -CR 312/5-2); Italy: Istituto Nazionale di Fisica Nucleare (ICSC, NextGenerationEU), Ministero dell'Universita e della Ricerca (PRIN -20223N7F8K -PNRR M4.C2.1.1); Japan: Japan Society for the Promotion of Science (JSPS KAKENHI JP21H05085, JSPS KAKENHI JP22H01227, JSPS KAKENHI JP22H04944, JSPS KAKENHI JP22KK0227); Netherlands: Netherlands Organization for Scientific Research (NWO Veni 2020 -VI.Veni.202.179); Norway: Research Council of Norway (RCN-314472); Poland: Polish National Agency for Academic Exchange (PPN/PPO/2020/1/00002/U/00001), Polish National Science Centre (NCN 2021/42/E/ST2/00350, NCN OPUS nr 2022/47/B/ST2/03059, NCN UMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, UMO-2021/40/C/ST2/00187, UMO-2022/47/O/ST2/00148); Slovenia: Slovenian Research Agency (ARIS grant J1-3010); Spain: BBVA Foundation (LEO22-1-603), Generalitat Valenciana, Spain (Artemisa, FEDER, IDIFEDER/2018/048), Ministry of Science and Innovation (MCIN ; NextGenEU PCI2022-135018-2, MICIN ; FEDER PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273-I, RYC2022-038164-I), PROMETEO and GenT Programmes Generalitat Valenciana (CIDEGENT/2019/023, CIDEGENT/2019/027); Sweden: Swedish Research Council (VR 2018-00482, VR 2022-03845, VR 2022-04683, VR grant 2021-03651), Knut and Alice Wallenberg Foundation, Sweden (KAW 2017.0100, KAW 2018.0157, KAW 2018.0458, KAW 2019.0447, KAW 2022.0358); Switzerland: Swiss National Science Foundation (SNSF -PCEFP2_194658); United Kingdom: Leverhulme Trust (Leverhulme Trust RPG-2020-004), Royal Society, United Kingdom (NIF-R1-231091); United States of America: U.S. Department of Energy (ECA DE-AC02-76SF00515), Neubauer Family Foundation
GKF ABBİ, KKF ABBİ Ve EKK ABBİ Yöntemlerinin Kıyaslanması
No full textIsik UniversityThe accuracy and reliability of GNSS (Global Navigation Satellite System) positioning are crucial, particularly in safety-critical applications, as well as in the aviation and defense industries. One of the methods used to enhance positioning accuracy and improve system reliability is Receiver Autonomous Integrity Monitoring (RAIM). In this study, three different RAIM methods were compared using both real-world and simulator-generated data in static and dynamic scenarios. To the best of our knowledge, no prior study in the literature has conducted such a comparison incorporating both real and simulated data. The results indicate that the RAIM method based on the Unscented Kalman Filter (UKF) exhibits significantly lower performance compared to the RAIM methods based on the Least Squares (LS) approach and the Extended Kalman Filter (EKF). © 2025 Elsevier B.V., All rights reserved
Measurements of W+w− Production Cross-Sections in Pp Collisions at S=13 TeV with the ATLAS Detector
No full textMeasurements of W+W− → e±νμ∓ν production cross-sections are presented, providing a test of the predictions of perturbative quantum chromodynamics and the electroweak theory. The measurements are based on data from pp collisions at s = 13 TeV recorded by the ATLAS detector at the Large Hadron Collider in 2015–2018, corresponding to an integrated luminosity of 140 fb−1. The number of events due to top-quark pair production, the largest background, is reduced by rejecting events containing jets with b-hadron decays. An improved methodology for estimating the remaining top-quark background enables a precise measurement of W+W− cross-sections with no additional requirements on jets. The fiducial W+W− cross-section is determined in a maximum-likelihood fit with an uncertainty of 3.1%. The measurement is extrapolated to the full phase space, resulting in a total W+W− cross-section of 127 ± 4 pb. Differential cross-sections are measured as a function of twelve observables that comprehensively describe the kinematics of W+W− events. The measurements are compared with state-of-the-art theory calculations and excellent agreement with predictions is observed. A charge asymmetry in the lepton rapidity is observed as a function of the dilepton invariant mass, in agreement with the Standard Model expectation. A CP-odd observable is measured to be consistent with no CP violation. Limits on Standard Model effective field theory Wilson coefficients in the Warsaw basis are obtained from the differential cross-sections. © 2025 Elsevier B.V., All rights reserved
Measurement of Double-Differential Charged-Current Drell-Yan Cross-Sections at High Transverse Masses in pp Collisions at √s=13 TeV with the ATLAS Detector
No full textBarakat, Marawan/0000-0001-5740-1866; Bhatta, Somadutta/0000-0002-9045-3278; Ernani Martins Neto, Daniel/0000-0003-2793-5335; Abbott, Braden/0000-0002-5888-2734; Jackson, Paul/0000-0002-0847-402X; Quinn, Ryan/0000-0002-0879-6045; Rompotis, Nikolaos/0000-0003-2577-1875; Camplani, Alessandra/0000-0002-6386-9788; Cheong, Sanha/0000-0002-2797-6383; Aboulhorma, Asmaa/0000-0002-9987-2292; Koffas, Thomas/0000-0001-9612-4988; Petersen, Troels/0000-0003-0221-3037; Angerami, Aaron/0000-0001-7834-8750; White, Martin/0000-0001-5474-4580; Camarda, Stefano/0000-0003-0479-7689; Gwilliam, Carl/0000-0002-9401-5304; Carmignani, Joseph (Joe)/0000-0002-1705-1061; Jia, Jiangyong/0000-0002-5725-3397; Hoppesch, Matthew/0000-0002-7773-3654; Das, Sruthy Jyothi/0000-0003-2693-3389; Bona, Marcella/0000-0002-9660-580X; Meloni, Federico/0000-0001-7075-2214; Vecchio, Valentina/0000-0002-1351-6757; Chu, Ming-Chung/0000-0002-1971-0403; Affolder, Anthony/0000-0002-9058-7217; Abicht, Nils Julius/0000-0001-5763-2760; Abdelhameed, Sara/0000-0002-0287-5869; Onyisi, Peter/0000-0003-4201-7997; Montella, Alessandro/0000-0002-5578-6333; Sadrozinski, Hartmut/0000-0003-0019-5410; Dinu, Ioan-Mihail/0000-0002-2683-7349; Sampsonidou, Despoina/0000-0003-0384-7672; Kretzschmar, Jan/0000-0002-8515-1355; Mlinarevic, Marin/0000-0003-3587-646X; Abramowicz, Halina/0000-0001-5329-6640; Ghosh, Aishik/0000-0003-0819-1553; Yabsley, Bruce/0000-0002-2680-0474; Chan, Jay/0000-0001-7069-0295; Vigl, Matthias/0000-0003-2281-3822; Mitsou, Vasiliki A./0000-0002-1533-8886; Aad, Georges/0000-0002-6665-4934; Kowalewski, Robert/0000-0002-7314-0990; Varvell, Kevin/0000-0003-1017-1295; Doglioni, Caterina/0000-0002-1509-0390; Volkotrub, Yuriy/0000-0002-3114-3798; Panizzo, Giancarlo/0000-0002-0352-4833; Stark, Giordon/0000-0001-6616-3433; Umaka, Ejiro/0000-0001-7725-8227; Chwastowski, Janusz/0000-0002-6190-8376; Islam, Wasikul/0000-0002-5624-5934; Haley, Joseph/0000-0002-6938-7405; Warburton, Andreas/0000-0002-2298-7315; Beretta, Matteo Mario/0000-0002-7026-8171; Moser, Brian/0000-0001-6750-5060This paper presents a first measurement of the cross-section for the charged-current Drell-Yan process pp -> W-+/- -> l(+/-)nu above the resonance region, where l is an electron or muon. The measurement is performed for transverse masses, m(T)(W), between 200 GeV and 5000 GeV, using a sample of 140 fb(-1) of pp collision data at a centre-of-mass energy of root s = 13 TeV collected by the ATLAS detector at the LHC during 2015-2018. The data are presented single differentially in transverse mass and double differentially in transverse mass and absolute lepton pseudorapidity. A test of lepton flavour universality shows no significant deviations from the Standard Model. The electron and muon channel measurements are combined to achieve a total experimental precision of 3% at low m(T)(W). The single- and double differential W-boson charge asymmetries are evaluated from the measurements. A comparison to next-to-next-to-leading-order perturbative QCD predictions using several recent parton distribution functions and including next-to-leading-order electroweak effects indicates the potential of the data to constrain parton distribution functions. The data are also used to constrain four fermion operators in the Standard Model Effective Field Theory formalism, in particular the lepton-quark operator Wilson coefficient c(lq)((3)).CERN; NDGF (Denmark, Norway, Sweden); KIT/GridKA (Germany); INFN-CNAF (Italy); NL-T1; BNL (U.S.A.); ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW; FWF, Austria; ANAS; CNPq; FAPESP, Brazil; NSERC; CFI, Canada; NSFC, China; MEYS CR, Czech Republic; DNRF; DNSRC, Denmark; IN2P3-CNRS; CEA-DRF/IRFU, France; BMBF; MPG, Germany; RGC and Hong Kong SAR, China; ICHEP; Academy of Sciences and Humanities, Israel; INFN, Italy; MEXT; JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW, Poland; FCT, Portugal; MNE/IFA, Romania; MSSR, Slovakia; Wallenberg Foundation, Sweden; SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; STFC/UKRI, United Kingdom; DOE; NSF, United States of America; BCKDF; CANARIE; CRC; DRAC, Canada; FORTE [CZ.02.01.01/00/22_008/0004632]; PRIMUS, Czech Republic; ERC [101116429]; ERDF; Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex; ANR, France; DFG; AvH Foundation, Germany - EU-ESF; Greek NSRF, Greece; BSF-NSF; NCN; La Caixa Banking Foundation; CERCA Programme Generalitat de Catalunya; PROMETEO; Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; Royal Society [NIF-R1-231091, ECA DE-AC02-76SF00515]; Leverhulme Trust, United Kingdom; Armenia: Yerevan Physics Institute (FAPERJ); CERN: European Organization for Nuclear Research; Chile: Agencia Nacional de Investigacion y Desarrollo (FONDECYT) [1230812]; FONDECYT [1240864]; China: Chinese Ministry of Science and Technology [MOST-2023YFA1605700, MOST-2023YFA1609300]; National Natural Science Foundation of China [NSFC -12175119, NSFC 12275265]; Czech Republic: Czech Science Foundation; Ministry of Education Youth and Sports [ERC-CZ-LL2327]; PRIMUS Research Programme [PRIMUS/21/SCI/017]; EU [ERC - 101002463]; European Union: European Research Council [ERC - 948254, 101089007]; European Regional Development Fund (SMASH COFUND) [101081355, CHIST-ERA-19-XAI00]; European Union [FAIR-NextGenerationEU PE00000013, EuroHPC - EHPC-DEV-2024D11-051]; France: Agence Nationale de la Recherche [ANR-21-CE31-0013, ANR-21-CE31-0022]; Germany: Baden-Wurttemberg Stiftung; Deutsche Forschungsgemeinschaft [DFG - 469666862, DFG - CR 312/52]; China: Research Grants Council (GRF); Ministero dell'Universita e della Ricerca; Japan Society for the Promotion of Science (JSPS KAKENHI) [JP22H01227, JP22H04944, JP22KK0227, JP23KK0245, RCN-314472, 9722]; Polish National Science Centre (NCN) [2021/42/E/ST2/00350]; NCN OPUS [2022/47/B/ST2/03059, UMO-2020/37/B/ST2/01043, UMO-2022/47/O/ST2/00148, UMO-2023/49/B/ST2/04085, UMO-2023/51/B/ST2/00920, UMO-2024/53/N/ST2/00869]; Generalitat Valenciana; FEDER [IDIFEDER/2018/048, NextGenEU PCI2022-135018-2]; MICIN FEDER [PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273-I, RYC2022-038164I]; Swedish Research Council (Swedish Research Council) [2023-04654, VR 2021-03651, VR 2022-03845, VR 2022-04683, VR 2023-03403, VR 2024-05451]; Knut and Alice Wallenberg Foundation [KAW 2018.0458, KAW 2022.0358, SNSF -PCEFP2_194658]; United Kingdom: Leverhulme Trust (Leverhulme Trust) [RPG-2020-004]We thank CERN for the very successful operation of the LHC and its injectors, as well as the support staff at CERN and at our institutions worldwide without whom ATLAS could not be operated efficiently. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF/SFU (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in ref. [102]. We gratefully acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MEYS CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ICHEP and Academy of Sciences and Humanities, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW, Poland; FCT, Portugal; MNE/IFA, Romania; MSTDI, Serbia; MSSR, Slovakia; ARIS and MVZI, Slovenia; DSI/NRF, South Africa; MICIU/AEI, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; NSTC, Taipei; TENMAK, Turkiye; STFC/UKRI, United Kingdom; DOE and NSF, United States of America. Individual groups and members have received support from BCKDF, CANARIE, CRC and DRAC, Canada; CERN-CZ, FORTE and PRIMUS, Czech Republic; COST, ERC, ERDF, Horizon 2020, ICSC-NextGenerationEU and Marie Sklodowska-Curie Actions, European Union; Investissements d'Avenir Labex, Investissements d'Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and MINERVA, Israel; NCN and NAWA, Poland; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. In addition, individual members wish to acknowledge support from Armenia: Yerevan Physics Institute (FAPERJ); CERN: European Organization for Nuclear Research (CERN DOCT); Chile: Agencia Nacional de Investigacion y Desarrollo (FONDECYT 1230812, FONDECYT 1230987, FONDECYT 1240864); China: Chinese Ministry of Science and Technology (MOST-2023YFA1605700, MOST-2023YFA1609300), National Natural Science Foundation of China (NSFC -12175119, NSFC 12275265); Czech Republic: Czech Science Foundation (GACR -24-11373S), Ministry of Education Youth and Sports (ERC-CZ-LL2327, FORTE CZ.02.01.01/00/22_008/0004632), PRIMUS Research Programme (PRIMUS/21/SCI/017); EU: H2020 European Research Council (ERC - 101002463); European Union: European Research Council (ERC - 948254, ERC 101089007, ERC, BARD, 101116429), European Regional Development Fund (SMASH COFUND 101081355, SLO ERDF), Horizon 2020 Framework Programme (MUCCA - CHIST-ERA-19-XAI00), European Union, Future Artificial Intelligence Research (FAIR-NextGenerationEU PE00000013), Horizon 2020 (EuroHPC - EHPC-DEV-2024D11-051), Italian Center for High Performance Computing, Big Data and Quantum Computing (ICSC, NextGenerationEU); France: Agence Nationale de la Recherche (ANR-21-CE31-0013, ANR-21-CE31-0022, ANR-22-EDIR-0002); Germany: Baden-Wurttemberg Stiftung (BW Stiftung-Postdoc Eliteprogramme), Deutsche Forschungsgemeinschaft (DFG - 469666862, DFG - CR 312/52); China: Research Grants Council (GRF); Italy: Istituto Nazionale di Fisica Nucleare (ICSC, NextGenerationEU), Ministero dell'Universita e della Ricerca (NextGenEU I53D23000820006 M4C2.1.1); Japan: Japan Society for the Promotion of Science (JSPS KAKENHI JP22H01227, JSPS KAKENHI JP22H04944, JSPS KAKENHI JP22KK0227, JSPS KAKENHI JP23KK0245); Norway: Research Council of Norway (RCN-314472); Poland: Ministry of Science and Higher Education (IDUB AGH, POB8, D4 no 9722), Polish National Science Centre (NCN 2021/42/E/ST2/00350, NCN OPUS 2023/51/B/ST2/02507, NCN OPUS nr 2022/47/B/ST2/03059, NCN UMO-2019/34/E/ST2/00393, UMO-2020/37/B/ST2/01043, UMO-2022/47/O/ST2/00148, UMO-2023/49/B/ST2/04085, UMO-2023/51/B/ST2/00920, UMO-2024/53/N/ST2/00869); Portugal: Foundation for Science and Technology (FCT); Spain: Generalitat Valenciana (Artemisa, FEDER, IDIFEDER/2018/048), Ministry of Science and Innovation (MCIN ; NextGenEU PCI2022-135018-2, MICIN ; FEDER PID2021-125273NB, RYC2019-028510-I, RYC2020-030254-I, RYC2021-031273-I, RYC2022-038164I); Sweden: Carl Trygger Foundation (Carl Trygger Foundation CTS 22:2312), Swedish Research Council (Swedish Research Council 2023-04654, VR 2021-03651, VR 2022-03845, VR 2022-04683, VR 2023-03403, VR 2024-05451), Knut and Alice Wallenberg Foundation (KAW 2018.0458, KAW 2022.0358, KAW 2023.0366); Switzerland: Swiss National Science Foundation (SNSF -PCEFP2_194658); United Kingdom: Leverhulme Trust (Leverhulme Trust RPG-2020-004), Royal Society (NIF-R1-231091); United States of America: U.S. Department of Energy (ECA DE-AC02-76SF00515), Neubauer Family Foundation
A Critical Challenge in the Heart Transplant Process: Left Ventricular Assist Device Infections
No full textObjective: This study aimed to investigate infections, microbiological agents, and factors affecting mortality in patients with end-stage heart failure who underwent left ventricular assist device (LVAD) surgery at our hospital since 2012, providing insights into patient follow-up and treatment strategies. Methods: This cross-sectional and retrospective study included 88 patients who underwent LVAD surgery at our hospital between 2012 and 2023 and subsequently developed infections. LVAD-specific and non-specific infections were classified according to the 2024 criteria of the International Society for Heart and Lung Transplantation (ISHLT). Results: A total of 88 patients who underwent LVAD implantation were included in the study. The mean age at implantation was 49.51 +/- 14.07 years, and the mean time to infection development was 17.90 +/- 13.55 months. Infections were observed in 94.3% of patients, while 45.4% developed sepsis and 53.4% had systemic inflammatory response syndrome (SIRS). The rate of intensive care unit admissions was 75.0%. Among the patients, 12.5% underwent debridement, 10.2% required complete device removal, and 6.8% underwent device exchange. The number of patients who underwent heart transplantation was 11, while 65 patients died. A total of 252 infection episodes were identified in 83 patients. The most common LVAD-specific infection was percutaneous driveline infection (40.8%). The most frequently observed clinical findings were discharge and fever, while Staphylococcus aureus and coagulase-negative staphylococci were the most commonly isolated pathogens. Nasal S. aureus carriage was detected in 27 (10.7%) patients, and among these, 16 (59.3%) patients developed S. aureus infections, which was statistically significant (p=0.001). Among Gram-negative bacteria, Pseudomonas aeruginosa and Escherichia coli were the most commonly isolated pathogens. Multidrug resistance (MDR) was observed in 35.4% of cases, while extended-spectrum beta-lactamase (ESBL) production was detected in 19.4%. Elevated creatinine levels, hypoalbuminemia, SIRS, and sepsis were found to be significantly associated with mortality (p0.05). Additionally, age, Pitt bacteremia score, and Charlson comorbidity index were significantly higher in deceased patients, while INTERMACS scores were significantly lower (p0.05). Conclusion: This study, conducted in patients with LVADs who have highly complex clinical conditions, provides significant insights into infection rates and factors influencing mortality. Our findings will contribute to future patient follow-up strategies and advanced-level research in this field
Facile and Scalable Synthesis of Crystalline BiOI Nanoflake Films via LiTFSI-Assisted Conversion of Porous BiI3 for Functional Applications
No full textBismuth oxyiodide (BiOI) has garnered significant attention due to its unique morphological, optical and electronic properties, making it a promising candidate for diverse applications in optoelectronics and energy-related fields. In this study, we report a novel and facile method for synthesizing crystalline BiOI nanoflake films via lithium bis(trifluoromethanesulfonyl)imide (LiTFSI)-assisted conversion of porous bismuth triiodide (BiI3) precursors. The synthesis involves formulating a stable BiI3 paste using LiTFSI as a structural template and gamma-butyrolactone (GBL) or dimethyl sulfoxide (DMSO) as solvents. The paste is deposited on flat substrates to form a film and subsequently hydrolyzed in deionized water under mild conditions, yielding BiOI films. The paste-based approach enables efficient material utilization and reproducible large-area synthesis. The resulting BiOI films were systematically characterized using scanning electron microscopy, X-ray diffraction, ultraviolet-visible spectroscopy, photoluminescence spectroscopy, Raman spectroscopy, Fourier transform infrared spectroscopy, Brunauer-Emmett-Teller surface area analysis and pore size distribution measurements. The films synthesized using GBL and DMSO exhibited well-defined nanoflake morphology, with average flake thicknesses of 24.3 and 17.5 nm, direct bandgap values of 2.07 and 1.95 eV, and surface areas of 19.57 and 16.71 m2/g, respectively. This robust and versatile synthesis strategy offers a promising pathway for the scalable production of high-quality BiOI films toward future optoelectronic and environmental photocatalytic applications.Scientific and Technological Research Council of Turkiye, TUBITAK [TUBITAK 224M021]This work was supported by the Scientific and Technological Research Council of Turkiye, TUBITAK (Project Number: TUBITAK 224M021). The authors would like to thank Prof. Dr. Nuri Durlu for kindly allowing the use of the XRD and SEM instruments, and Dr. F ; imath;rat Memu for his valuable assistance
The Performance of Missing Transverse Momentum Reconstruction and Its Significance with the ATLAS Detector Using 140 fb-1 of S=13 TeV pp Collisions
No full textThis paper presents the reconstruction of missing transverse momentum (pTmiss) in proton–proton collisions, at a center-of-mass energy of 13 TeV. This is a challenging task involving many detector inputs, combining fully calibrated electrons, muons, photons, hadronically decaying τ-leptons, hadronic jets, and soft activity from remaining tracks. Possible double counting of momentum is avoided by applying a signal ambiguity resolution procedure which rejects detector inputs that have already been used. Several pTmiss ‘working points’ are defined with varying stringency of selections, the tightest improving the resolution at high pile-up by up to 39% compared to the loosest. The pTmiss performance is evaluated using data and Monte Carlo simulation, with an emphasis on understanding the impact of pile-up, primarily using events consistent with leptonic Z decays. The studies use 140fb-1 of data, collected by the ATLAS experiment at the Large Hadron Collider between 2015 and 2018. The results demonstrate that pTmiss reconstruction, and its associated significance, are well understood and reliably modelled by simulation. Finally, the systematic uncertainties on the soft pTmiss component are calculated. After various improvements the scale and resolution uncertainties are reduced by up to 76% and 51%, respectively, compared to the previous calculation at a lower luminosity. © 2025 Elsevier B.V., All rights reserved
Strain-Modulated Conductivity and Work Function on Thin Crystals of Mo2C
No full textThin transition metal carbides (TMCs) exhibit a favorable combination of electronic and mechanical properties that makes them attractive for applications ranging from flexible energy storage to electromagnetic shielding. However, the influence of strain on key electronic characteristics such as conductivity and work function has not yet been elucidated. Here, we present a combined experimental and computational study of surface electronics on thin crystals of molybdenum carbide (Mo2C). Conductive atomic force microscopy (C-AFM) and Kelvin probe force microscopy (KPFM) performed on rippled regions of crystal surfaces reveal a significant increase in electrical conductivity and a notable reduction in work function under tensile strains of 1% and below. Ab initio calculations confirm the trends observed in the experiments, pointing toward increased density of states (DOS), enhanced mobility, and reduced work function under tensile strain. Our work highlights the potential of strain engineering for tuning the electronic characteristics of thin TMCs.U.S. Department of Defense [FA9550-22-1-0358, FA9550-18-1-7048, FA9550-22-1-0418]; Air Force Office of Scientific Research (AFOSR)This work was supported by the Air Force Office of Scientific Research (AFOSR) Award No. FA9550-22-1-0358, FA9550-18-1-7048, and FA9550-22-1-0418
Static and Dynamic Pupillary Changes Reflect Autonomic Effects of Acute Sleep Deprivation in Healthy Adults
No full textAim To assess the pupillary activity and sympathetic skin responses of acute sleep-deprived participants (= 4 h) by comparing these values with non-sleep-deprived controls (>7 h). Methods This study included 39 participants, comprising 23 from the sleep deprivation group and 16 from the healthy control group. Self-reported sleep duration, the Karolinska Sleepiness Scale (KSS), and the Epworth Sleepiness Scale (ESS) were used to evaluate the state of sleepiness. Static and dynamic pupillometry measurements using the Sirius topography device, the amplitude of accommodation using Tonoref III, and sympathetic skin responses quantified via EMG were examined. Results The mean scotopic and mesopic pupil diameters were higher in acute sleep-deprived participants compared to controls (6.33 +/- 0.59 vs 6.05 +/- 0.51, P = 0.030 for scotopic luminance; 5.28 +/- 0.69 vs 5.00 +/- 0.46, P = 0.047 for mesopic luminance, respectively). In dynamic pupillometry, the speed of pupil dilation in the sleep deprivation group was higher than in the control group (0.22 +/- 0.03 vs 0.20 +/- 0.03, P = 0.004). The photopic pupil diameter, accommodation amplitude, and sympathetic skin responses were similar between the groups (P > 0.05). While sleep duration was inversely correlated with pupil diameters under all luminances, the ESS score was positively correlated with mesopic and photopic pupil diameters (P 0.05 for each). Conclusions Acute sleep deprivation alters both static and dynamic pupil responses, reflecting autonomic changes, whereas sympathetic skin responses remained unaffected. Even a single day of partial sleep deprivation is capable of impairing pupillary responses
İnsansız Helikopter Hava Aracının Platform Seviyesi Güvenilirlik Analizi
No full textFazlı görev güvenilirliği analizi, teknolojik sistemlerin artan karmaşıklığı ve birden fazla fazı içeren görevlere olan ihtiyaç nedeniyle önem kazanmıştır. 1970'li yıllardan itibaren başta havacılık olmak üzere birçok alanda fazlı görev güvenilirliği çalışmaları ön plana çıkmaktadır. Bu tez çalışmasında, insansız helikopter platformunun fazlı görev güvenilirliği analizine yönelik bir model geliştirilmiştir. Çalışma yürütülürken platformun görevi fazlara bölünmüş ve her bir fazın motor, yakıt, iniş takımı ve seyrüsefer sistemlerinin hata türleri belirlenmiştir. Her bir faz ve alt sistemlere ait hata türleri Hata Türleri ve Etkileri Analizi (HTEA) ile değerlendirilmiş ve Hata Ağacı Analizi (FTA) yöntemi kullanılarak hata olasılıkları hesaplanmıştır. Analiz sürecinde, PTC Windchill yazılımı kullanılarak sistemlerin hata oranları hesaplanmış ve fazlara göre değişen güvenilirlik seviyeleri ortaya konmuştur. Üç farklı görev fazı (kalkış, seyir, iniş) boyunca hata senaryoları oluşturulmuş ve bu senaryolara bağlı olarak faz güvenilirlik değerleri elde edilmiştir. Her bir sistemin kendine özgü hata türleri belirlenerek, faz güvenilirlik değerleri birleştirilmiş ve platformun genel güvenilirliği hesaplanmıştır. Bu çalışma, fazlı görev güvenilirliği kavramının insansız hava araçları özelinde nasıl uygulanabileceğini ortaya koymakta ve hata analizi yöntemlerinin bu tür sistemlerde nasıl kullanılabileceğini göstermektedir. Sonuç olarak, insansız hava araçlarının sistem güvenilirliğini artırmak için faz bazlı analizlerin önemini vurgulayan bu çalışma, mühendislik projelerinde uygulanabilir yöntemler sunmaktadır.Phase mission reliability analysis has gained significance due to the increasing complexity of technological systems and the need for missions involving multiple phases. Since 1970s, phase mission reliability studies have been at the forefront, particularly in the aviation industry. This thesis develops a phase mission reliability analysis model for an unmanned helicopter platform. The mission is divided into phases, and the failure modes of the engine, fuel, landing gear, and navigation systems for each phase are identified. These failure modes are evaluated using Failure Modes and Effects Analysis (FMEA) and analyzed using the Fault Tree Analysis (FTA) method to calculate failure probabilities. During the analysis process, PTC Windchill software is employed to compute system failure rates and determine reliability levels across different phases. Failure scenarios are created for three distinct mission phases (takeoff, cruise, and landing), and reliability values are obtained accordingly. The unique failure modes of each system are identified, phase-specific reliability values are aggregated, and the overall reliability of the platform is determined. This study demonstrates how phase mission reliability can be applied specifically to unmanned aerial vehicles (UAVs) and illustrates how failure analysis methods can be effectively utilized for such systems. Ultimately, this research highlights the importance of phase-based analysis in enhancing the reliability of UAV systems and provides practical methodologies applicable to engineering project